一、概述

go的pprof工具可以用来监测进程的运行数据，用于监控程序的性能，对内存使用和CPU使用的情况统信息进行分析。

官方提供了两个包：runtime/pprof和net/http/pprof，前者用于普通代码的性能分析，后者用于web服务器的性能分析。

官方文档：

https://golang.org/pkg/runtime/pprof/

https://golang.org/pkg/net/http/pprof/#Index

https://github.com/google/pprof/blob/master/doc/pprof.md

二、runtime/pprof的使用

该包提供了一系列用于调试信息的方法，可以很方便的对堆栈进行调试。

通常用得多得是以下几个：

• StartCPUProfile：开始监控cpu。
• StopCPUProfile：停止监控cpu，使用StartCPUProfile后一定要调用该函数停止监控。
• WriteHeapProfile：把堆中的内存分配信息写入分析文件中。

示例代码

package main

import (
    "flag"
    "runtime/pprof"
    "log"
    "runtime"
    "math/rand"
    "os"
    "time"
)

var cpuprofile = flag.String("cpuprofile", "", "write cpu profile `file`")
var memprofile = flag.String("memprofile", "", "write memory profile to `file`")

const (
    col = 10000
    row = 10000
)

func main() {
    flag.Parse()
    if *cpuprofile != "" {
        f, err := os.Create(*cpuprofile)
        if err != nil {
            log.Fatal("could not create CPU profile: ", err)
        }
        if err := pprof.StartCPUProfile(f); err != nil {  //监控cpu
            log.Fatal("could not start CPU profile: ", err)
        }
        defer pprof.StopCPUProfile()
    }

    // 主逻辑区，进行一些简单的代码运算
    x := [row][col]int{}
    s := rand.New(rand.NewSource(time.Now().UnixNano()))

    for i := 0; i < row; i++{
        for j := 0; j < col; j++ {
            x[i][j] = s.Intn(100000)
        }
    }


    for i := 0; i < row; i++{
        tmp := 0
        for j := 0; j < col; j++ {
            tmp += x[i][j]
        }
    }


    if *memprofile != "" {
        f, err := os.Create(*memprofile)
        if err != nil {
            log.Fatal("could not create memory profile: ", err)
        }
        runtime.GC() // GC，获取最新的数据信息
        if err := pprof.WriteHeapProfile(f); err != nil {  // 写入内存信息
            log.Fatal("could not write memory profile: ", err)
        }
        f.Close()
    }
}

编译运行，会根据入参生成两个对应的数据文件：

> go build
> ./pprof -cpuprofile cpu.prof -memprofile mem.prof
> ll
total 2656
-rw-r--r--. 1 ma root    1183 Jan  9 21:39 cpu.prof  # cpu运行数据
-rw-r--r--. 1 ma root     280 Jan  9 21:39 mem.prof  # 内存数据
-rwxr-xr-x. 1 ma root 2707088 Jan  9 21:39 pprof  # 编译后的可执行文件
-rw-r--r--. 1 ma root    1296 Jan  9 21:38 pprof.go

使用go tool pprof命令即可分析。

三、go tool pprof

生成数据文件后使用go tool pprof file进入交互式界面进行数据分析，输入help可以查看命令。

用法详见：pprof.md

> go tool pprof cpu.prof
Entering interactive mode (type "help" for commands)
(pprof) help

 Commands:
   cmd [n] [--cum] [focus_regex]* [-ignore_regex]*
       Produce a text report with the top n entries.
       Include samples matching focus_regex, and exclude ignore_regex.
       Add --cum to sort using cumulative data.
       Available commands:
         callgrind    Outputs a graph in callgrind format
         disasm       Output annotated assembly for functions matching regexp or address
         dot          Outputs a graph in DOT format
         eog          Visualize graph through eog
         evince       Visualize graph through evince
         gif          Outputs a graph image in GIF format
         gv           Visualize graph through gv
         list         Output annotated source for functions matching regexp
         pdf          Outputs a graph in PDF format
         peek         Output callers/callees of functions matching regexp
         png          Outputs a graph image in PNG format
         proto        Outputs the profile in compressed protobuf format
         ps           Outputs a graph in PS format
         raw          Outputs a text representation of the raw profile
         svg          Outputs a graph in SVG format
         tags         Outputs all tags in the profile
         text         Outputs top entries in text form
         top          Outputs top entries in text form
         tree         Outputs a text rendering of call graph
         web          Visualize graph through web browser
         weblist      Output annotated source in HTML for functions matching regexp or address
   peek func_regex
       Display callers and callees of functions matching func_regex.
...

1.top

命令格式：top [n]，查看排名前n个数据，默认为10。

(pprof) top
8490ms of 8510ms total (99.76%)
Dropped 13 nodes (cum <= 42.55ms)
Showing top 10 nodes out of 15 (cum >= 110ms)
      flat  flat%   sum%        cum   cum%
    6780ms 79.67% 79.67%     8510ms   100%  main.main
     670ms  7.87% 87.54%     1250ms 14.69%  math/rand.(*Rand).Int31n
     350ms  4.11% 91.66%     1600ms 18.80%  math/rand.(*Rand).Intn
     260ms  3.06% 94.71%      580ms  6.82%  math/rand.(*Rand).Int31
     190ms  2.23% 96.94%      190ms  2.23%  math/rand.(*rngSource).Int63
     130ms  1.53% 98.47%      320ms  3.76%  math/rand.(*Rand).Int63
     110ms  1.29% 99.76%      110ms  1.29%  runtime.memclrNoHeapPointers
         0     0% 99.76%     8510ms   100%  runtime.goexit
         0     0% 99.76%      110ms  1.29%  runtime.heapBits.initSpan
         0     0% 99.76%      110ms  1.29%  runtime.largeAlloc

2.tree

命令格式：tree [n]，以树状图形式显示，默认显示10个。

(pprof) tree 5
8250ms of 8510ms total (96.94%)
Dropped 13 nodes (cum <= 42.55ms)
Showing top 5 nodes out of 15 (cum >= 190ms)
----------------------------------------------------------+-------------
      flat  flat%   sum%        cum   cum%   calls calls% + context
----------------------------------------------------------+-------------
    6780ms 79.67% 79.67%     8510ms   100%                | main.main
                                            1600ms   100% |   math/rand.(*Rand).Intn
----------------------------------------------------------+-------------
                                            1250ms   100% |   math/rand.(*Rand).Intn
     670ms  7.87% 87.54%     1250ms 14.69%                | math/rand.(*Rand).Int31n
                                             580ms   100% |   math/rand.(*Rand).Int31
----------------------------------------------------------+-------------
                                            1600ms   100% |   main.main
     350ms  4.11% 91.66%     1600ms 18.80%                | math/rand.(*Rand).Intn
                                            1250ms   100% |   math/rand.(*Rand).Int31n
----------------------------------------------------------+-------------
                                             580ms   100% |   math/rand.(*Rand).Int31n
     260ms  3.06% 94.71%      580ms  6.82%                | math/rand.(*Rand).Int31
                                             190ms   100% |   math/rand.(*rngSource).Int63
----------------------------------------------------------+-------------
                                             190ms   100% |   math/rand.(*Rand).Int31
     190ms  2.23% 96.94%      190ms  2.23%                | math/rand.(*rngSource).Int63
----------------------------------------------------------+-------------

3.web

以web形式查看，在web服务的时候经常被用到，需要安装gv工具，官方网页：http://www.graphviz.org/。

linux用户使用yum install graphviz安装即可，当然，纯命令行界面是不能查看的。

windows用户下载msi包安装后需要把安装目录下的bin目录添加到环境变量才行。

如果没有安装gv工具，使用会报错：

Cannot find dot, have you installed Graphviz?

exec: “firefox”: executable file not found in $PATH

4.其他

其他的都是以不同形式展现出来，大同小异，以后有时间再测试。

四、web服务器监测

在web服务器中监测只需要在import部分加上监测包即可：

import(
    _ "net/http/pprof"
)

当服务开启后，在当前服务环境的http://ip:port/debug/pprof页面可以看到当前的系统信息：

点击查看具体的信息：

通常可以对服务器在一段时间内进行数据采样，然后分析服务器的耗时和性能:

go tool pprof http://*:*/debug/pprof/profile

使用该命令后会对服务进行30s的采样，这段时间内可以尽量多使用web服务，生成多一些统计数据。

> go tool pprof http://127.0.0.1:8080/debug/pprof/profile
Fetching profile from http://127.0.0.1:8080/debug/pprof/profile
Please wait... (30s)
Saved profile in \pprof\pprof.127.0.0.1.samples.cpu.001.pb.gz
Entering interactive mode (type "help" for commands)
(pprof) top
3870ms of 4800ms total (80.62%)
Dropped 37 nodes (cum <= 24ms)
Showing top 10 nodes out of 66 (cum >= 110ms)
      flat  flat%   sum%        cum   cum%
    1230ms 25.62% 25.62%     1300ms 27.08%  runtime.mapaccess1_faststr
     860ms 17.92% 43.54%      860ms 17.92%  runtime.memclrNoHeapPointers
     810ms 16.88% 60.42%     1010ms 21.04%  runtime.scanobject
     190ms  3.96% 64.38%      190ms  3.96%  runtime.heapBitsForObject
     160ms  3.33% 67.71%      190ms  3.96%  strconv.ParseInt
     140ms  2.92% 70.62%     1720ms 35.83%  business_sets/haoxingdai_qiangdan/server/handler.makeOrder4Replace
     140ms  2.92% 73.54%     1990ms 41.46%  runtime.mallocgc
     120ms  2.50% 76.04%      120ms  2.50%  runtime.heapBitsSetType
     110ms  2.29% 78.33%     1680ms 35.00%  runtime.mapassign
     110ms  2.29% 80.62%      110ms  2.29%  runtime.memhash

使用web命令后会生成采样时间内每个系统调用的耗时分析，可以用来分析web服务的响应时间都用在哪了：